Name
Title | ||
|---|---|---|
A Neural Approach To Unsupervised Classification Of Very-High Resolution Polarimetric Sar Data |
Abstract | ||
|---|---|---|
Analysis of L-band polarimetric SAR data has not been extensively carried out for undulating, heterogeneous and fragmented landscapes, where classification can become quite challenging. This paper reports results of a study on the pixel-by-pixel unsupervised classification of very-high resolution polarimetric images by self-organizing neural networks. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/IGARSS.2007.4423767 | IGARSS: 2007 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-12: SENSING AND UNDERSTANDING OUR PLANET |
Keywords | Field | DocType |
SAR, classification, SOM (Self-Organizing Maps) | Terrain mapping,Computer vision,Polarimetry,Computer science,Remote sensing,Unsupervised learning,Artificial intelligence,Polarimetric sar,Pixel,Artificial neural network | Conference |
ISSN | Citations | PageRank |
2153-6996 | 4 | 0.94 |
References | Authors | |
5 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alessandro Burini | 1 | 11 | 3.13 |
| Cosimo Putignano | 2 | 8 | 3.16 |
| Fabio Del Frate | 3 | 508 | 72.43 |
| Marco Del Greco | 4 | 6 | 1.35 |
| Giovanni Schiavon | 5 | 123 | 24.55 |
| Domenico Solimini | 6 | 65 | 15.10 |